In this study, we found that sarcopenia is a strong risk factor for reduced treatment regimens, treatment discontinuation, and diminished PFS in glioblastoma patients. We suggest that sarcopenic patients may profit from enhanced follow-up and expedited palliative care access.

Our work is based on a prior proof-of-concept study in glioblastoma patients. It demonstrated that radiation planning CTs could be used for body composition measures at C1, that these measures were representative of whole-body measurements, and that muscle measures were associated with OS in glioblastoma patients [11].

In this follow-up study in an enlarged and updated patient cohort, we investigated whether body composition parameters were clinically valuable for identifying patients at risk for adverse treatment courses. Here, we a priori defined patients in the lowest quartile of muscle measurements as sarcopenic. While predefined cutoffs for sarcopenic patients are available at multiple levels in the trunk [10], no data exist regarding the neck. Subsequently, we defined a cohort-based cutoff, similar to previous studies [18]. Based on this setup, we drew multiple key conclusions, which are discussed in the following sections.

The American Society for Radiation Oncology (ASTRO) guideline [19] suggests age-stratified glioblastoma treatment with hypofractionated radiotherapy recommended for patients older than 70 years. The guideline’s authors note that age cutoff values may differ substantially between studies and many subgroup analyses are small and retrospective in nature [19]. Age also remains an imperfect variable given variation in physical functioning, quality of life, and prognosis between patients of similar age [20, 21]. Elderly patients with good physical functioning may indeed profit from chemoradiotherapy as opposed to radiotherapy alone [22]. Thus, the authors also suggest stratifying by “performance status” to better individualize treatment recommendations [19]. However, Karnofsky index and ECOG score are prone to high interrater variability [23, 24].

As a quantitative, non-rater-dependent biomarker, sarcopenia measurements incorporate both age and performance status [25]. Sarcopenia becomes more prevalent with age [25] and is negatively associated with physical functioning [5]. Some studies refer to body composition parameters as measures of “biologic age” as they encompass nutritional factors, functioning, inflammation, and chronological age [26]. This is reflected in our findings, as sarcopenia was associated with these factors in our cohort: Significant associations were found for chronological age, BMI, comorbidities, and ECOG score. The strongest signal was found for ECOG, demonstrating a close association between sarcopenia and (reduced) physical functioning, as expected [27]. Notably, whether sarcopenia is the result of a limited physical status or vice versa remains unclear, as the retrospective nature of our study allows for tests regarding association, but not causation. In any case, sarcopenia is a quantitative marker related to numerous otherwise difficult-to-quantify parameters.

Importantly, as discussed above, sarcopenia is associated with key treatment stratification parameters from the ASTRO guideline. Consistent with this, sarcopenic patients were less likely to receive the standard chemoradiotherapy treatment and more likely to undergo hypofractionated irradiation without chemotherapy in our study. Interestingly, despite abbreviated and de-escalated treatment prescription, patients still discontinued radiotherapy at a higher rate. This underlines the need for reduced treatment paradigms in sarcopenic patients. Hence, sarcopenia may be a potential prospective marker that helps guide treatment decision-making.

It is well known that elderly patients are at risk for increased treatment toxicities, most prominently from chemotherapy [28]. Treating younger patients with poor performance status also remains a major concern, yet data are more limited [29].

Sarcopenic patients were more often prescribed corticosteroids during treatment (64% vs. 49%). Steroids may change body composition measures in the long term [30] and aggravate sarcopenia. However, this is unlikely to have affected our measurements, as radiation planning CTs are commonly performed within weeks after primary diagnosis and neurosurgical evaluation, and before application of radiotherapy. Our data indicate that sarcopenic patients may be more at risk for brain edema symptoms, as these trigger corticosteroid therapy during radiation.

While chemoradiotherapy discontinuation was increased among sarcopenic patients, 85% of sarcopenic patients still completed the prescribed therapy. We believe our data suggest that sarcopenic patients may profit from more intensive medical care during therapy. However, the relatively high completion rate of radiotherapy among sarcopenic patients may support continued use of postoperative radiotherapy (with the potential omission of chemotherapy) in this group, similar to findings from the ASTRO guideline for elderly patients or those with low performance status [19]. However, our study is retrospective in nature and this question may only be definitively answered in prospective trials.

Upon treatment completion, a small subpopulation of patients were directly transferred to in-patient palliative care, likely indicative of limited outcomes. While these patients were overrepresented among sarcopenic patients (11% vs. 5%), the vast majority of sarcopenic patients, 80%, returned home after treatment. Sarcopenia may nonetheless help to identify patients who could profit from intensified, and early, palliative care interventions.

The associations between sarcopenia and OS [31, 32] or complications [33,34,35] have been well described in numerous malignancies. Most studies imply that reduced physical functioning (commonly associated with sarcopenia [5]) is likely to make patients more susceptible to developing complications, limiting survival [36].

In our study, sarcopenic glioblastoma patients were more likely to show early progression. This is an intriguing finding, as PFS (different from OS) is likely not directly associated with reduced physical functioning. We initially hypothesized that treatment discontinuation in sarcopenic patients may induce early progression, similar to other malignancies [37]. However, while treatment was more limited in some sarcopenic patients, nearly three quarters of sarcopenic patients received full standard chemoradiotherapy treatment. Thus, we considered differences in treatment completion or chemotherapy application as unlikely to account for the drastic difference in PFS across the entire sarcopenic population (median PFS 5.1 vs. 8.4 months). When assessing this hypothesis, we were reluctant to include chemoradiotherapy treatment completion in our multivariable PFS model as we aimed to only include parameters available at the onset of postoperative treatment. Chemotherapy discontinuation may be advised during treatment depending on blood test results [38]. Hence, we generated a second, separate multivariable model and only included patients who completed standard chemoradiotherapy. In this homogeneously treated cohort, the strong association between sarcopenia and PFS remained unchanged. Consequently, we concluded that the link between sarcopenia and PFS was not mediated via treatment discontinuation.

Similarly, sarcopenic patients did not show differences in tumor characteristics or resection status, making it unlikely that these factors confounded our findings. Notably, tumor volume at diagnosis was slightly increased in sarcopenic patients, raising questions regarding the interplay between increased tumor growth and a rising incidence of sarcopenia. This association has been confirmed in different tumor entities [39]. However, despite inclusion of tumor volume in our multivariable model, sarcopenia was independently associated with PFS. Interestingly, residual tumor volume was not significantly different between the groups after resection.

Thus, after careful consideration of potential clinical confounders, we believe that sarcopenia is instead likely to be associated with PFS via biological factors. In other tumor entities, these include sarcopenia-related immune senescence [40] and proinflammatory signaling [41]. In glioblastoma, immunosuppression increases treatment resistance [42, 43] and induces a distinct neuroinflammatory microenvironment that promotes tumor growth and invasion [44]. In lung cancer, immunotherapy (which is not part of standard treatment in glioblastoma patients) showed a substantially reduced efficacy in sarcopenic patients, potentially indicative of an altered baseline immune system in this group [45]. Prospective studies have linked sarcopenia to systemic inflammation and a distinct disbalance in the immune system [46].

We suspect that sarcopenic glioblastoma patients are a subgroup of patients with an unfavorable inflammatory and immune status. This may potentially promote tumor progression, leading to the reduction in PFS we see in the sarcopenic subgroup.

Clinically, this finding is meaningful, as the optimal follow-up intervals for glioblastoma patients remain unclear [47]. In the absence of specific evidence, MRIs are commonly scheduled every 12 weeks following intra-institutional pragmatic considerations [47, 48]. Novel computational studies try to predict individualized time to progression to optimize this decision [49]. Here, sarcopenia may be a valuable parameter. Our study indicates that it may be reasonable for sarcopenic patients to undergo more frequent follow-up imaging, e.g., every 8 weeks. However, given moderate tolerance of primary treatment and aggressive tumor growth in sarcopenic patients, the clinical benefit of sometimes intensive retreatment [50] in this vulnerable subgroup might be debatable and should be considered with care. Notably, our measurements—which become available only postsurgically—are neither designed nor intended to change the role of up-front surgical resection, which remains the gold standard for virtually all glioblastoma patients.

As expected, based on the previous exploratory study [11], our increased cohort again shows a convincing association with overall survival, both in univariable and multivariable modeling. Different from the previous study, we used our novel sarcopenia definition in this analysis (as opposed to simply dividing a cohort by the median, as done in the exploratory stage). The strong difference in median survival of roughly 6 months demonstrates that our sarcopenic measurements have identified an at-risk cohort with good selectivity.

CT-based measurements are universally attainable in radiotherapy patients. The diversification of the glioma diagnosis based on methylation profiling and gene expression [51, 52] will increase the need for commonly available parameters to identify populations in which treatment escalation or de-escalation is advisable. This was also reflected in a recent post-hoc analysis of the CATNON trial [53], questioning the concurrent use of TMZ in adjuvant glioblastoma radiotherapy, and the lack of a clear treatment standard for patients with relapsed disease. Identifying sarcopenia early might help to guide treatment decisions in different prognostic groups and stages of treatment. End-to-end pipelines for automation of measurements have been built and may facilitate clinical implementation [54]. Automated scoring results (e.g., percentiles based on the overall patient cohort) may then be considered for therapeutic decision-making. However, prospective data collection and validation needs to precede any assessment of clinical application.

Sarcopenia may be modifiable to some degree, mainly through changes in nutrition and physical activity [55]. However, whether these interventions improve outcomes remains unclear. Our study indicates that patients with very low muscle measurements would potentially profit most from interventions. However, these patients may suffer from neurologic symptoms, such as hemiplegia, limiting the potential for physical exercise. Nonetheless, we believe that past and ongoing physical exercise [56,57,58] and nutritional investigations [59] in glioblastoma patients have merit.

Some study limitations should be noted. First, this is a retrospective monocentric analysis with the corresponding risk of bias. However, we included a large cohort of patients and patient characteristics were largely representative of the overall glioblastoma population. Nonetheless, we remain unable to address prospective questions such as the modifiability of sarcopenia. Second, multivariable modeling was not possible for treatment application and tolerance outcomes due to high treatment adherence and low complication rates. However, multivariable modeling was performed for PFS. Third, PFS was not available in all patients. However, a large majority of patients, more than 70%, had available PFS. Fourth, semi-automated segmentations required some manual correction, potentially limiting clinical application. However, body composition measurements have been shown to be automatable thanks to novel computational methods [60]. Finally, MRI-based radiation planning may alleviate the need for cranial planning CTs in the future, preventing opportunistic sarcopenia measurements. However, while technically more challenging, sarcopenia measures are also feasible on MRI imaging [61].